Overview

Dataset statistics

Number of variables11
Number of observations1000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory86.1 KiB
Average record size in memory88.1 B

Variable types

NUM10
BOOL1

Warnings

X0 has unique values Unique
X1 has unique values Unique
X2 has unique values Unique
X3 has unique values Unique
X4 has unique values Unique
X5 has unique values Unique
X6 has unique values Unique
X7 has unique values Unique
X8 has unique values Unique
X9 has unique values Unique

Reproduction

Analysis started2020-12-15 20:10:28.775987
Analysis finished2020-12-15 20:10:52.237859
Duration23.46 seconds
Software versionpandas-profiling v2.9.0
Download configurationconfig.yaml

Variables

X0
Real number (ℝ)

UNIQUE

Distinct1000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-0.01097635057
Minimum-3.721674841
Maximum2.697962156
Zeros0
Zeros (%)0.0%
Memory size7.9 KiB
2020-12-15T21:10:52.343352image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum-3.721674841
5-th percentile-1.655721553
Q1-0.665895623
median0.004500820399
Q30.649852315
95-th percentile1.534055332
Maximum2.697962156
Range6.419636997
Interquartile range (IQR)1.315747938

Descriptive statistics

Standard deviation0.9742033679
Coefficient of variation (CV)-88.75476065
Kurtosis-0.09878121708
Mean-0.01097635057
Median Absolute Deviation (MAD)0.6580292197
Skewness-0.1206116083
Sum-10.97635057
Variance0.9490722021
MonotocityNot monotonic
2020-12-15T21:10:52.707255image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
0.299933205210.1%
 
-0.607523044610.1%
 
1.88459335510.1%
 
-0.233574807410.1%
 
-1.53166459910.1%
 
0.698092165910.1%
 
-0.313424235210.1%
 
0.475139152910.1%
 
1.13722609910.1%
 
-1.68124891210.1%
 
1.85838785910.1%
 
-0.720550970410.1%
 
1.3599909110.1%
 
-2.54969957810.1%
 
-1.08439706410.1%
 
1.2931093110.1%
 
-1.66139105910.1%
 
-1.19395963110.1%
 
1.37538193610.1%
 
-0.74293237410.1%
 
-1.08480596810.1%
 
-1.1598120210.1%
 
-0.592799471510.1%
 
-0.997505158310.1%
 
1.1787407110.1%
 
Other values (975)97597.5%
 
ValueCountFrequency (%) 
-3.72167484110.1%
 
-3.13784565910.1%
 
-2.67997083410.1%
 
-2.63848733710.1%
 
-2.57961166410.1%
 
-2.54969957810.1%
 
-2.37927752710.1%
 
-2.32161037210.1%
 
-2.28203454510.1%
 
-2.23220363110.1%
 
ValueCountFrequency (%) 
2.69796215610.1%
 
2.54048948110.1%
 
2.52357129710.1%
 
2.49421178410.1%
 
2.39378768810.1%
 
2.3885333210.1%
 
2.31432719210.1%
 
2.28989350210.1%
 
2.26730039810.1%
 
2.19225397310.1%
 

X1
Real number (ℝ)

UNIQUE

Distinct1000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.01981967543
Minimum-3.373852947
Maximum3.233791157
Zeros0
Zeros (%)0.0%
Memory size7.9 KiB
2020-12-15T21:10:52.937633image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum-3.373852947
5-th percentile-1.564611023
Q1-0.6587331729
median-0.008012547739
Q30.6550283905
95-th percentile1.798149332
Maximum3.233791157
Range6.607644104
Interquartile range (IQR)1.313761563

Descriptive statistics

Standard deviation1.008162049
Coefficient of variation (CV)50.8667285
Kurtosis0.1964317794
Mean0.01981967543
Median Absolute Deviation (MAD)0.6540244121
Skewness0.1032893588
Sum19.81967543
Variance1.016390718
MonotocityNot monotonic
2020-12-15T21:10:53.157353image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
-0.358819112110.1%
 
1.97199583610.1%
 
-0.683302447710.1%
 
1.01093315410.1%
 
1.90217960510.1%
 
0.0945380295510.1%
 
-0.033047227310.1%
 
-1.31191217110.1%
 
-0.023773330710.1%
 
-0.422842622210.1%
 
0.702293109610.1%
 
1.07484136210.1%
 
-0.46132834810.1%
 
-0.232945105410.1%
 
-0.0732890492110.1%
 
-0.108226132110.1%
 
-0.0272853955710.1%
 
0.370928809610.1%
 
0.99513946410.1%
 
-1.33772955410.1%
 
-0.277200275510.1%
 
0.141370447610.1%
 
-1.11421370310.1%
 
1.7832450710.1%
 
-1.59473390310.1%
 
Other values (975)97597.5%
 
ValueCountFrequency (%) 
-3.37385294710.1%
 
-3.32113115910.1%
 
-3.18109156210.1%
 
-2.7248670810.1%
 
-2.54753666910.1%
 
-2.4794289610.1%
 
-2.47494844210.1%
 
-2.43839795610.1%
 
-2.37589468210.1%
 
-2.36877149210.1%
 
ValueCountFrequency (%) 
3.23379115710.1%
 
3.13076607210.1%
 
3.03975172310.1%
 
3.0303866210.1%
 
2.90745334210.1%
 
2.71249666210.1%
 
2.58183627510.1%
 
2.58173615210.1%
 
2.54836581310.1%
 
2.53115936810.1%
 

X2
Real number (ℝ)

UNIQUE

Distinct1000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.05365760773
Minimum-3.792757084
Maximum3.356494662
Zeros0
Zeros (%)0.0%
Memory size7.9 KiB
2020-12-15T21:10:53.398216image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum-3.792757084
5-th percentile-1.61286016
Q1-0.6525026612
median0.06688833021
Q30.7436120937
95-th percentile1.773793693
Maximum3.356494662
Range7.149251746
Interquartile range (IQR)1.396114755

Descriptive statistics

Standard deviation1.022505181
Coefficient of variation (CV)19.05610825
Kurtosis-0.004503350507
Mean0.05365760773
Median Absolute Deviation (MAD)0.701432925
Skewness-0.02661326771
Sum53.65760773
Variance1.045516846
MonotocityNot monotonic
2020-12-15T21:10:53.624214image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
-1.31210660510.1%
 
-0.320898597910.1%
 
0.945901645610.1%
 
0.0783987072610.1%
 
0.789107030910.1%
 
0.734846969510.1%
 
-0.0162882776110.1%
 
0.179310234910.1%
 
1.42742286210.1%
 
0.999555707110.1%
 
-0.0870916383110.1%
 
-0.108282016810.1%
 
0.0732258981110.1%
 
0.837575652310.1%
 
0.134921070510.1%
 
0.334948973910.1%
 
-2.93307161410.1%
 
1.98832532410.1%
 
0.33815591210.1%
 
0.815182792710.1%
 
0.187489681610.1%
 
0.575830680610.1%
 
0.044459625410.1%
 
0.637608947710.1%
 
0.309567081310.1%
 
Other values (975)97597.5%
 
ValueCountFrequency (%) 
-3.79275708410.1%
 
-2.93307161410.1%
 
-2.88533995110.1%
 
-2.66869328410.1%
 
-2.56248354110.1%
 
-2.52088707210.1%
 
-2.49454153410.1%
 
-2.35080963510.1%
 
-2.34254322510.1%
 
-2.28594968910.1%
 
ValueCountFrequency (%) 
3.35649466210.1%
 
3.11286117610.1%
 
2.75097334510.1%
 
2.72040374710.1%
 
2.69739091210.1%
 
2.5851481110.1%
 
2.46161808210.1%
 
2.42464996610.1%
 
2.4079600310.1%
 
2.39557481110.1%
 

X3
Real number (ℝ)

UNIQUE

Distinct1000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.008552089225
Minimum-2.738198967
Maximum2.894218367
Zeros0
Zeros (%)0.0%
Memory size7.9 KiB
2020-12-15T21:10:53.853889image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum-2.738198967
5-th percentile-1.657050729
Q1-0.6820282175
median0.001072777769
Q30.6863016855
95-th percentile1.808014711
Maximum2.894218367
Range5.632417333
Interquartile range (IQR)1.368329903

Descriptive statistics

Standard deviation1.01007903
Coefficient of variation (CV)118.1090379
Kurtosis-0.2018683718
Mean0.008552089225
Median Absolute Deviation (MAD)0.6860659221
Skewness0.0793128616
Sum8.552089225
Variance1.020259648
MonotocityNot monotonic
2020-12-15T21:10:54.057168image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
-1.40220582110.1%
 
-0.191809557710.1%
 
-0.423231087510.1%
 
1.45347055610.1%
 
0.433186931410.1%
 
0.916700292210.1%
 
-2.62731748210.1%
 
0.577039307110.1%
 
0.756148557910.1%
 
0.391867689910.1%
 
0.356554394610.1%
 
0.719655074210.1%
 
-0.526005287910.1%
 
1.31199502110.1%
 
-1.27167916910.1%
 
0.974222108610.1%
 
-0.0580517975310.1%
 
-1.09750469810.1%
 
-1.14409412710.1%
 
-0.480337713910.1%
 
0.361469785910.1%
 
-0.547062181610.1%
 
-0.065890685610.1%
 
-0.631427913510.1%
 
-1.11921492910.1%
 
Other values (975)97597.5%
 
ValueCountFrequency (%) 
-2.73819896710.1%
 
-2.62731748210.1%
 
-2.49172012910.1%
 
-2.48175302210.1%
 
-2.47760598810.1%
 
-2.35249542910.1%
 
-2.32881883610.1%
 
-2.28484938210.1%
 
-2.27436270210.1%
 
-2.27247010210.1%
 
ValueCountFrequency (%) 
2.89421836710.1%
 
2.81856260210.1%
 
2.79447129110.1%
 
2.64715226910.1%
 
2.63985408210.1%
 
2.55277372910.1%
 
2.50596639710.1%
 
2.50550858510.1%
 
2.36925602610.1%
 
2.34265378710.1%
 

X4
Real number (ℝ)

UNIQUE

Distinct1000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-0.0213764267
Minimum-3.389254946
Maximum3.569576014
Zeros0
Zeros (%)0.0%
Memory size7.9 KiB
2020-12-15T21:10:54.276141image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum-3.389254946
5-th percentile-1.59909986
Q1-0.6253399199
median-0.05323232516
Q30.6078025024
95-th percentile1.477287713
Maximum3.569576014
Range6.958830959
Interquartile range (IQR)1.233142422

Descriptive statistics

Standard deviation0.935382474
Coefficient of variation (CV)-43.75766292
Kurtosis0.1795555383
Mean-0.0213764267
Median Absolute Deviation (MAD)0.6297520876
Skewness-0.01058593326
Sum-21.3764267
Variance0.8749403726
MonotocityNot monotonic
2020-12-15T21:10:54.491571image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
-2.28193270210.1%
 
0.113234372710.1%
 
0.823374832410.1%
 
0.564406243110.1%
 
0.070641254610.1%
 
0.773810377410.1%
 
0.53253332810.1%
 
-1.23273368810.1%
 
-0.438525552210.1%
 
-0.174782610210.1%
 
-0.292808455610.1%
 
-1.56872149310.1%
 
0.385234578110.1%
 
0.922007286110.1%
 
0.229362196210.1%
 
0.681332761510.1%
 
0.580998954910.1%
 
-1.23155984210.1%
 
-1.71168860910.1%
 
-0.612157572510.1%
 
-0.801188535510.1%
 
0.477518807510.1%
 
0.57467141410.1%
 
-0.295390485210.1%
 
-1.46842902610.1%
 
Other values (975)97597.5%
 
ValueCountFrequency (%) 
-3.38925494610.1%
 
-3.10206513110.1%
 
-2.98306779510.1%
 
-2.65259240110.1%
 
-2.57622304110.1%
 
-2.46035496410.1%
 
-2.28193270210.1%
 
-2.23444207410.1%
 
-2.1749774710.1%
 
-2.13593177410.1%
 
ValueCountFrequency (%) 
3.56957601410.1%
 
2.76818761110.1%
 
2.57750670410.1%
 
2.46469938110.1%
 
2.44988498810.1%
 
2.42037551610.1%
 
2.34857575710.1%
 
2.33819979510.1%
 
2.28505842910.1%
 
2.2666890310.1%
 

X5
Real number (ℝ)

UNIQUE

Distinct1000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-0.08705227012
Minimum-3.009534793
Maximum2.744438615
Zeros0
Zeros (%)0.0%
Memory size7.9 KiB
2020-12-15T21:10:54.719269image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum-3.009534793
5-th percentile-1.676424866
Q1-0.7835596349
median-0.1206385322
Q30.5895206132
95-th percentile1.589413814
Maximum2.744438615
Range5.753973408
Interquartile range (IQR)1.373080248

Descriptive statistics

Standard deviation1.01370474
Coefficient of variation (CV)-11.64478237
Kurtosis-0.004490395358
Mean-0.08705227012
Median Absolute Deviation (MAD)0.684495155
Skewness0.05463316074
Sum-87.05227012
Variance1.0275973
MonotocityNot monotonic
2020-12-15T21:10:54.918750image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
-0.12535911310.1%
 
0.732767595310.1%
 
2.02160067410.1%
 
-1.34100505910.1%
 
-0.272212961910.1%
 
-0.236841440610.1%
 
0.235581277710.1%
 
-0.565178618410.1%
 
0.387116397510.1%
 
-0.949255239210.1%
 
1.06742650310.1%
 
0.399555981710.1%
 
0.00464277199710.1%
 
-0.825403931310.1%
 
-0.793823113210.1%
 
-0.5609145710.1%
 
0.575277410310.1%
 
-0.229674943710.1%
 
-0.797271749610.1%
 
-0.673313371910.1%
 
0.011250500810.1%
 
-1.25620175510.1%
 
-0.449226821710.1%
 
-0.435389488810.1%
 
0.790412411910.1%
 
Other values (975)97597.5%
 
ValueCountFrequency (%) 
-3.00953479310.1%
 
-2.93233117410.1%
 
-2.89095626710.1%
 
-2.82125081510.1%
 
-2.8089199210.1%
 
-2.77410499510.1%
 
-2.74397491510.1%
 
-2.71132547110.1%
 
-2.69854759110.1%
 
-2.65552981610.1%
 
ValueCountFrequency (%) 
2.74443861510.1%
 
2.62854131410.1%
 
2.61493897110.1%
 
2.49122640810.1%
 
2.4864929810.1%
 
2.44241325610.1%
 
2.42911835310.1%
 
2.41723297610.1%
 
2.39135424310.1%
 
2.34677189310.1%
 

X6
Real number (ℝ)

UNIQUE

Distinct1000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-0.02594470769
Minimum-3.32346669
Maximum2.967437846
Zeros0
Zeros (%)0.0%
Memory size7.9 KiB
2020-12-15T21:10:55.137134image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum-3.32346669
5-th percentile-1.609027505
Q1-0.6919848979
median-0.06421742304
Q30.697580731
95-th percentile1.556132138
Maximum2.967437846
Range6.290904536
Interquartile range (IQR)1.389565629

Descriptive statistics

Standard deviation0.9977369415
Coefficient of variation (CV)-38.45627993
Kurtosis0.0101108216
Mean-0.02594470769
Median Absolute Deviation (MAD)0.7020281132
Skewness-0.03013492762
Sum-25.94470769
Variance0.9954790044
MonotocityNot monotonic
2020-12-15T21:10:55.345033image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
1.253591710.1%
 
0.946691769610.1%
 
-0.909276034510.1%
 
0.178964695110.1%
 
0.582592254210.1%
 
-0.137392495510.1%
 
-0.93221538910.1%
 
-1.89900656610.1%
 
-0.00832039944710.1%
 
1.30802306410.1%
 
0.606256584110.1%
 
-0.645305954910.1%
 
-1.11747827510.1%
 
0.0286892618110.1%
 
0.0174515495210.1%
 
0.95102750210.1%
 
0.338215615910.1%
 
-0.634989954210.1%
 
1.15458267110.1%
 
-2.03231225410.1%
 
1.14710247210.1%
 
-1.58443294210.1%
 
-0.154894202610.1%
 
-1.47987390710.1%
 
0.514682855510.1%
 
Other values (975)97597.5%
 
ValueCountFrequency (%) 
-3.3234666910.1%
 
-3.23412146310.1%
 
-3.02029061610.1%
 
-3.00035888810.1%
 
-2.69963422410.1%
 
-2.69834484110.1%
 
-2.63151204110.1%
 
-2.61248430410.1%
 
-2.54112442110.1%
 
-2.53405742510.1%
 
ValueCountFrequency (%) 
2.96743784610.1%
 
2.91000248610.1%
 
2.82512329110.1%
 
2.73421014910.1%
 
2.47407708910.1%
 
2.46398643410.1%
 
2.44327069310.1%
 
2.28883839410.1%
 
2.27762309510.1%
 
2.25845947210.1%
 

X7
Real number (ℝ)

UNIQUE

Distinct1000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-0.01208505987
Minimum-3.23510646
Maximum2.724670615
Zeros0
Zeros (%)0.0%
Memory size7.9 KiB
2020-12-15T21:10:55.712693image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum-3.23510646
5-th percentile-1.662105919
Q1-0.6416767864
median-0.009294654433
Q30.6758852588
95-th percentile1.583679228
Maximum2.724670615
Range5.959777075
Interquartile range (IQR)1.317562045

Descriptive statistics

Standard deviation0.9971264981
Coefficient of variation (CV)-82.50902427
Kurtosis0.09027811295
Mean-0.01208505987
Median Absolute Deviation (MAD)0.6681086632
Skewness-0.06314616332
Sum-12.08505987
Variance0.9942612532
MonotocityNot monotonic
2020-12-15T21:10:55.926721image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
0.659704379810.1%
 
-0.281351319510.1%
 
0.213264246110.1%
 
1.22642739710.1%
 
1.1035444810.1%
 
1.15827748110.1%
 
0.886319967110.1%
 
-0.784919914510.1%
 
-0.508311906910.1%
 
-0.638328474610.1%
 
-1.71759590210.1%
 
-2.81278335610.1%
 
1.12035603110.1%
 
-0.098797440410.1%
 
-0.889591578710.1%
 
-1.32871842110.1%
 
-0.197307496510.1%
 
0.287955626310.1%
 
0.27380260410.1%
 
-0.128368506910.1%
 
0.723835578510.1%
 
-0.072754657110.1%
 
1.05444090310.1%
 
0.466523643110.1%
 
-0.734985266410.1%
 
Other values (975)97597.5%
 
ValueCountFrequency (%) 
-3.2351064610.1%
 
-3.11051781410.1%
 
-2.81278335610.1%
 
-2.81077003910.1%
 
-2.71026608910.1%
 
-2.64822896710.1%
 
-2.64526777810.1%
 
-2.63197857910.1%
 
-2.57121571810.1%
 
-2.57003434210.1%
 
ValueCountFrequency (%) 
2.72467061510.1%
 
2.68064731310.1%
 
2.65202104610.1%
 
2.63607775710.1%
 
2.56518686810.1%
 
2.4929941310.1%
 
2.45361822710.1%
 
2.45353758510.1%
 
2.42226715310.1%
 
2.41860690310.1%
 

X8
Real number (ℝ)

UNIQUE

Distinct1000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-0.02494844803
Minimum-3.028589149
Maximum3.175844647
Zeros0
Zeros (%)0.0%
Memory size7.9 KiB
2020-12-15T21:10:56.159837image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum-3.028589149
5-th percentile-1.581377637
Q1-0.6891890914
median0.001209437568
Q30.6080847123
95-th percentile1.558733721
Maximum3.175844647
Range6.204433796
Interquartile range (IQR)1.297273804

Descriptive statistics

Standard deviation0.9604557019
Coefficient of variation (CV)-38.49761319
Kurtosis-0.01223839644
Mean-0.02494844803
Median Absolute Deviation (MAD)0.6494068541
Skewness-0.02352896279
Sum-24.94844803
Variance0.9224751553
MonotocityNot monotonic
2020-12-15T21:10:56.369295image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
-0.869664885710.1%
 
0.738425621710.1%
 
0.317452474910.1%
 
2.2373062710.1%
 
0.938489503710.1%
 
-0.315980166110.1%
 
-1.74641917710.1%
 
-0.547102745910.1%
 
0.638951067710.1%
 
0.0734904033710.1%
 
0.416803301410.1%
 
-0.156564352410.1%
 
0.0562923939410.1%
 
0.0790854284610.1%
 
0.540798900910.1%
 
0.72646876210.1%
 
1.10864606410.1%
 
0.884791181410.1%
 
1.9082880110.1%
 
-0.0116438397510.1%
 
0.120322225710.1%
 
0.218602360210.1%
 
1.18529554210.1%
 
0.157733883410.1%
 
-0.355977508610.1%
 
Other values (975)97597.5%
 
ValueCountFrequency (%) 
-3.02858914910.1%
 
-2.6983567810.1%
 
-2.68639182310.1%
 
-2.65642657310.1%
 
-2.56181092110.1%
 
-2.52329524810.1%
 
-2.50961807210.1%
 
-2.4314029510.1%
 
-2.38785940610.1%
 
-2.35898545410.1%
 
ValueCountFrequency (%) 
3.17584464710.1%
 
2.67265975310.1%
 
2.62754958210.1%
 
2.60711239710.1%
 
2.4938489710.1%
 
2.46302675910.1%
 
2.35435179210.1%
 
2.2709102910.1%
 
2.2373062710.1%
 
2.21548126110.1%
 

X9
Real number (ℝ)

UNIQUE

Distinct1000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.01598046201
Minimum-3.839169171
Maximum2.983293427
Zeros0
Zeros (%)0.0%
Memory size7.9 KiB
2020-12-15T21:10:56.601914image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum-3.839169171
5-th percentile-1.616809333
Q1-0.6517896922
median-0.002503442754
Q30.6624172957
95-th percentile1.643671048
Maximum2.983293427
Range6.822462598
Interquartile range (IQR)1.314206988

Descriptive statistics

Standard deviation0.9886949077
Coefficient of variation (CV)61.86898146
Kurtosis0.08792174794
Mean0.01598046201
Median Absolute Deviation (MAD)0.6570866547
Skewness-0.04036592507
Sum15.98046201
Variance0.9775176206
MonotocityNot monotonic
2020-12-15T21:10:56.825646image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
-0.287691656710.1%
 
0.318162833210.1%
 
-0.0631631913510.1%
 
-0.319330482810.1%
 
0.797299433410.1%
 
-2.27077763410.1%
 
0.0681455221610.1%
 
1.38230202710.1%
 
-0.297148265610.1%
 
-0.0689191955210.1%
 
-1.10721239410.1%
 
1.09953083710.1%
 
0.536218778710.1%
 
-0.145989681610.1%
 
0.0217166178810.1%
 
-0.671728340410.1%
 
-1.67518561210.1%
 
0.409822083510.1%
 
-0.611358126810.1%
 
-1.30800270610.1%
 
1.64858974810.1%
 
-1.92280148710.1%
 
-1.27485503810.1%
 
-1.16914492810.1%
 
0.505021219310.1%
 
Other values (975)97597.5%
 
ValueCountFrequency (%) 
-3.83916917110.1%
 
-3.48315127410.1%
 
-3.08319839810.1%
 
-2.71252216110.1%
 
-2.55656146710.1%
 
-2.33387228810.1%
 
-2.31017692810.1%
 
-2.28503537610.1%
 
-2.27077763410.1%
 
-2.24758634210.1%
 
ValueCountFrequency (%) 
2.98329342710.1%
 
2.79021048110.1%
 
2.72555331910.1%
 
2.53242236310.1%
 
2.50695186610.1%
 
2.43930420410.1%
 
2.37850870410.1%
 
2.36867512410.1%
 
2.28983520810.1%
 
2.28973067210.1%
 

y
Boolean

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
1
500 
0
500 
ValueCountFrequency (%) 
150050.0%
 
050050.0%
 
2020-12-15T21:10:56.996039image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Interactions

2020-12-15T21:10:29.699890image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:10:29.915087image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:10:30.130486image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:10:30.355718image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:10:30.571205image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:10:30.789934image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:10:31.008557image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:10:31.227169image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:10:31.439286image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:10:31.655145image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:10:31.877449image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:10:32.095312image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:10:32.298791image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:10:32.505818image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:10:32.705598image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:10:32.912076image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:10:33.122387image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:10:33.321197image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:10:33.523457image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:10:33.730229image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:10:34.079347image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:10:34.299329image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:10:34.501216image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:10:34.721724image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:10:34.933698image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:10:35.142825image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:10:35.364690image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:10:35.574558image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:10:35.793222image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:10:36.012525image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:10:36.238093image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:10:36.451004image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:10:36.648242image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:10:36.869977image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:10:37.089501image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:10:37.296849image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:10:37.506097image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:10:37.712477image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:10:37.910302image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:10:38.221925image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:10:38.491550image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:10:38.692610image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:10:38.905806image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:10:39.122734image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:10:39.339429image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:10:39.548352image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:10:39.764286image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:10:39.973237image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:10:40.329961image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:10:40.544971image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:10:40.758301image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:10:40.965832image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:10:41.168911image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:10:41.388026image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:10:41.604082image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:10:41.805367image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:10:42.010401image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:10:42.218241image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:10:42.436714image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:10:42.648329image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:10:42.860422image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:10:43.074445image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:10:43.282739image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:10:43.494305image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:10:43.708145image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:10:43.918427image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:10:44.129232image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:10:44.336431image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:10:44.545502image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:10:44.757439image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:10:44.970044image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:10:45.178014image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:10:45.379965image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:10:45.597142image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:10:45.804901image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:10:46.016043image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:10:46.220677image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:10:46.561738image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:10:46.763009image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:10:46.975285image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:10:47.190962image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:10:47.403016image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:10:47.614668image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:10:47.835253image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:10:48.053727image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:10:48.252865image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:10:48.456738image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:10:48.668353image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:10:48.878471image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:10:49.095502image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:10:49.305430image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:10:49.534756image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:10:49.752875image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:10:49.978855image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:10:50.183408image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:10:50.394931image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:10:50.620533image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:10:50.845098image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:10:51.062284image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:10:51.279020image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Correlations

2020-12-15T21:10:57.112160image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2020-12-15T21:10:57.398953image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2020-12-15T21:10:57.687604image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2020-12-15T21:10:57.979982image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Missing values

2020-12-15T21:10:51.663590image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:10:52.031459image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Sample

First rows

X0X1X2X3X4X5X6X7X8X9y
00.203116-0.0666091.161229-0.3119210.7412550.1806180.189078-0.7596140.3189670.5888010
1-0.6692000.943179-1.553258-0.3325110.810452-0.0151650.1166520.175414-0.072502-0.4268081
2-1.0607311.731454-0.817621-0.666837-0.5302460.441397-1.1450200.0778101.7652590.6530861
3-2.079673-0.856513-1.5377170.8109820.3764280.2519110.553667-0.6229170.724897-1.2759691
41.1787410.934699-0.2112920.782933-0.4608241.0255460.995271-0.949554-0.561964-0.9537731
5-3.1378460.038718-0.7053760.525504-1.3071931.466797-1.478384-0.943908-0.6385661.5449081
6-1.7729690.591321-0.059549-0.391178-0.8955510.2786241.036550-0.9137810.055521-0.4546571
70.884740-2.2913441.676949-0.7323850.3700782.1809141.3400240.5610081.1852960.9933040
8-1.092110-1.116343-1.696489-1.0517950.822602-0.4726520.275876-0.546445-1.313002-0.0609611
9-0.0095420.599762-0.450982-1.1654150.1435050.5434220.329128-0.5428491.4185850.4809521

Last rows

X0X1X2X3X4X5X6X7X8X9y
9900.3014840.4569600.259444-1.4864600.2948870.5226750.8830310.874399-0.7298091.0199850
9911.2265290.511818-0.599115-0.4768320.3017351.349426-0.5820040.687164-0.6664421.8444210
992-1.4866640.511333-1.2743650.2437951.1704561.138438-0.888052-1.1407691.070421-1.8094871
9930.387014-1.108579-0.5629990.705522-1.8766150.228841-0.9438320.558426-0.4637521.6858850
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